Exponential Organisations - Book Review

Book - Exponential Organisations, Salim IsmailBook Review

Introduction

An Exponential Organization is one whose impact (or output) is disproportionally large – at least 10 x larger – compared to its peers because of the use of new organizational techniques that leverage accelerating technologies.

Ray Kurzweil, who has studied this phenomenon for thirty years, to make four signature observations:First, the doubling pattern identified by Gordon Moore in integrated circuits applies to any information technology. Kurzweil calls this the Law of Accelerating Returns (LOAR) and shows that doubling patterns in computation extend all the way back to 1900, far earlier than Moore’s original pronouncement.Second, the driver fuelling this phenomenon is information. Once any domain, discipline, technology or industry becomes information-enabled and powered by information flows, its price/performance begins doubling approximately annually.Third, once that doubling pattern starts, it doesn’t stop. We use current computers to design faster computers, which then build faster computers, and so on.

Finally, several key technologies today are now information-enabled and following the same trajectory.

Those technologies include:

artificial intelligence (AI),

robotics,

biotech and bioinformatics,

medicine,

neuroscience,

data science,

3D printing,

nanotechnology

and even aspects of energy

When facing exponential growth, the experts in almost every field always projected linearly, despite the evidence before their eyes.

Kurzweil took Moore’s Law several steps further, noting that every information-based paradigm operates in the same way, something he called the Law of Accelerating Returns (LOAR).

Ten years ago we had five hundred million Internet-connected devices, Today there are about eight billion.

By 2020 there will be fifty billion and a decade later we’ll have a trillion Internet-connected devices as we literally information-enable every aspect of the world in the Internet of Things.

The Internet is now the world’s nervous system, with our mobile devices serving as edge points and nodes on that network.

Think about that for a second: we’ll be jumping from eight billion Internet-connected devices today to fifty billion by 2025, and to a trillion a mere decade later.

We like to think that thirty or forty years into the Information Revolution we are well along in terms of its development.

But according to this metric, we’re just 1% of the way down the road.

Not only is most of that growth still ahead of us, all of it is. And everything is being disrupted in the process.

Indeed, those who have attempted it have found that the organization’s “immune system” is liable to respond to the perceived threat with an attack.

Two key factors enabled Waze to succeed, and those two factors hold true for all next-generation ExO companies:

Access resources you don’t own. In Waze’s case, the company made use of the GPS readings already on its users’ smartphones. Information is your greatest asset. More reliably than any other asset, information has the potential to double regularly. Rather than simply assembling assets, the key to success is accessing valuable caches of existing information.

The real, fundamental question of our exponential age is: What else can be information-enabled?

The key outcome when you access resources and information-enable them is that your marginal costs drop to zero.

Quite possibly the granddaddy of information-based ExOs is Google, which doesn’t own the web pages it scans. Its revenue model, the butt of many jokes ten years ago, has enabled Google to become a $400 billion company, a milestone it reached by essentially manipulating textual (and now video) information. LinkedIn and Facebook together are worth over $200 billion, and that’s just as a result of digitizing our relationships—that is, turning them into information.

CHAPTER THREE - The Exponential Organization

There’s a good reason for that: if a company thinks small, it is unlikely to pursue a business strategy that will achieve rapid growth.

TED: “Ideas worth spreading.”

Google: “Organize the world’s information.”

X Prize Foundation: “Bring about radical breakthroughs for the benefit of humanity.”

Quirky: “Make invention accessible.”

Singularity University: “Positively impact one billion people.”

None states what the organisation does, but rather what it aspires to accomplish.

The aspirations are neither narrow nor even technology-specific.

Rather, they aim to capture the hearts and minds—and imaginations and ambitions—of those both inside and (especially) outside the organization.

Some aim to transform the planet, others just an industry. But radical transformation is the name of the game.

The most important outcome of a proper MTP is that it generates a cultural movement—what John Hagel and John Seely Brown call the “Power of Pull.” That is, the MTP is so inspirational that a community forms around the ExO and spontaneously begins operating on its own, ultimately creating its own community, tribe and culture.Martin Seligman, a leading expert on positive psychology, differentiates between three states of happiness:

the pleasurable life (hedonistic, superficial)

the good life (family and friends)

and the meaningful life (finding purpose, transcending ego, working toward a higher good)

Five external characteristics that define an Exponential Organisation, for which we use the acronym SCALE:

Staff on Demand

Community & Crowd

Algorithms

Leveraged Assets

Engagement

Staff on Demand

The half-life of a learned skill used to be about thirty years.

Today it’s down to about five years.

In any information-enabled business large internal staff seem increasingly unnecessary, counterproductive and expensive.

Gigwalk, which relies on half a million smart-phone-enabled workers, offers an example of how this new world of employment works.

When Proctor and Gamble needs to know how and where its merchandise is being placed on Walmart shelves around the world, it can use Gigwalk’s platform to instantly deploy thousands of people who are paid a few dollars to walk into Walmart and check the shelves.

Results come in within an hour.

In years past, having a large workforce differentiated your enterprise and allowed it to accomplish more.

Today, that same large workforce can become an anchor that reduces manoeuvrability and slows you down.Community & Crowd

“If you build communities and you do things in public,” he says, “you don’t have to find the right people, they find you.”

“At the top of every one of these communities is a benevolent dictator.” You need strong leadership to manage the community, because although there are no employees, people still have responsibilities and need to be held accountable for their performances.

Already, ExOs are leveraging community and crowd for many functions traditionally handled inside the enterprise, including idea generation, funding, design, and distribution, marketing and sales.

This shift is powerful and taps into what university professor and social media guru Clay Shirky calls cognitive surplus. “The world has over a trillion hours a year of free time to commit to shared projects,” he said in a recent TED radio broadcast.

And that’s just today.

By 2020, when three billion additional minds using inexpensive tablets join the two billion currently online, Shirky’s trillion hours per year will triple.

Algorithms

Today, the world is pretty much run on algorithms.

From automotive anti-lock braking to Amazon’s recommendation engine; from dynamic pricing for airlines to predicting the success of upcoming Hollywood blockbusters; from writing news posts to air traffic control; from credit card fraud detection to the 2% of posts that Facebook shows a typical user—algorithms are everywhere in modern life.

Machine Learning is the ability to accurately perform new, unseen tasks, built on known properties learned from training or historic data, and based on prediction.

Deep Learning is a new and exciting subset of Machine Learning based on neural net technology. It allows a machine to discover new patterns without being exposed to any historical or training data.

In the same way that today we can no longer handle the complexities of air traffic control or supply chain management without algorithms, almost all the business insights and decisions of tomorrow will be data-driven.

AI and algorithms to mitigate and compensate for many of the following heuristics in human cognition:Anchoring bias: Tendency to rely too heavily, or “anchor,” on one trait or piece of information when making decisions.

Availability bias: Tendency to overestimate the likelihood of events with greater “availability” in memory, which can be influenced by how recent the memories are or how unusual or emotionally charged they may be.

Confirmation bias: Tendency to search for, interpret, focus on and remember information in a way that confirms one’s preconceptions.

Framing bias: Drawing different conclusions from the same information, depending on how or by whom that information is presented.

Optimism bias: Tendency to be over-optimistic, overestimating favourable and pleasing outcomes.Planning fallacy bias: Tendency to overestimate benefits and underestimate costs and task-completion times.Sunk-cost or loss-aversion bias: Dis-utility of giving up an object is greater than the utility associated with acquiring it.

Cognitive biases -

Name

Description

Ambiguity effect

The tendency to avoid options for which missing information makes the probability seem "unknown".

Anchoring or focalism

The tendency to rely too heavily, or "anchor", on one trait or piece of information when making decisions (usually the first piece of information acquired on that subject)

Anthropomorphism or personification

The tendency to characterize animals, objects, and abstract concepts as possessing human-like traits, emotions, and intentions.

Attentional bias

The tendency of our perception to be affected by our recurring thoughts.

Automation bias

The tendency to depend excessively on automated systems which can lead to erroneous automated information overriding correct decisions.

Availability heuristic

The tendency to overestimate the likelihood of events with greater "availability" in memory, which can be influenced by how recent the memories are or how unusual or emotionally charged they may be.

Availability cascade

A self-reinforcing process in which a collective belief gains more and more plausibility through its increasing repetition in public discourse (or "repeat something long enough and it will become true").

The tendency to assume that specific conditions are more probable than general ones.

Conservatism (belief revision)

The tendency to revise one's belief insufficiently when presented with new evidence.

Continued influence effect

The tendency to believe previously learned misinformation even after it has been corrected. Misinformation can still influence inferences one generates after a correction has occurred. cf. Backfire effect

Contrast effect

The enhancement or reduction of a certain perception's stimuli when compared with a recently observed, contrasting object.

Courtesy bias

The tendency to give an opinion that is more socially correct than one's true opinion, so as to avoid offending anyone.

Curse of knowledge

When better-informed people find it extremely difficult to think about problems from the perspective of lesser-informed people.

Declinism

The belief that a society or institution is tending towards decline. Particularly, it is the predisposition to view the past favourably (rosy retrospection) and future negatively.

Decoy effect

Preferences for either option A or B change in favor of option B when option C is presented, which is similar to option B but in no way better.

Denomination effect

The tendency to spend more money when it is denominated in small amounts (e.g., coins) rather than large amounts (e.g., bills).

Disposition effect

The tendency to sell an asset that has accumulated in value and resist selling an asset that has declined in value.

Distinction bias

The tendency to view two options as more dissimilar when evaluating them simultaneously than when evaluating them separately.

Dunning–Kruger effect

The tendency for unskilled individuals to overestimate their own ability and the tendency for experts to underestimate their own ability.

Duration neglect

The neglect of the duration of an episode in determining its value

Empathy gap

The tendency to underestimate the influence or strength of feelings, in either oneself or others.

Endowment effect

The tendency for people to demand much more to give up an object than they would be willing to pay to acquire it.

Exaggerated expectation

Based on the estimates, real-world evidence turns out to be less extreme than our expectations (conditionally inverse of the conservatism bias).unreliable source?

Experimenter's or expectation bias

The tendency for experimenters to believe, certify, and publish data that agree with their expectations for the outcome of an experiment, and to disbelieve, discard, or downgrade the corresponding weightings for data that appear to conflict with those expectations.

Focusing effect

The tendency to place too much importance on one aspect of an event.

Forer effect or Barnum effect

The observation that individuals will give high accuracy ratings to descriptions of their personality that supposedly are tailored specifically for them, but are in fact vague and general enough to apply to a wide range of people. This effect can provide a partial explanation for the widespread acceptance of some beliefs and practices, such as astrology, fortune telling, graphology, and some types of personality tests.

Framing effect

Drawing different conclusions from the same information, depending on how that information is presented

Frequency illusion

The illusion in which a word, a name, or other thing that has recently come to one's attention suddenly seems to appear with improbable frequency shortly afterwards (not to be confused with the recency illusion or selection bias). This illusion may explain some examples of the Baader-Meinhof Phenomenon, when someone repeatedly notices a newly learned word or phrase shortly after learning it.

Functional fixedness

Limits a person to using an object only in the way it is traditionally used.

Gambler's fallacy

The tendency to think that future probabilities are altered by past events, when in reality they are unchanged. The fallacy arises from an erroneous conceptualization of the law of large numbers. For example, "I've flipped heads with this coin five times consecutively, so the chance of tails coming out on the sixth flip is much greater than heads."

Hard–easy effect

Based on a specific level of task difficulty, the confidence in judgments is too conservative and not extreme enough

Hindsight bias

Sometimes called the "I-knew-it-all-along" effect, the tendency to see past events as being predictable at the time those events happened.

Hostile attribution bias

The "hostile attribution bias" is the tendency to interpret others' behaviors as having hostile intent, even when the behavior is ambiguous or benign.

Hot-hand fallacy

The "hot-hand fallacy" (also known as the "hot hand phenomenon" or "hot hand") is the fallacious belief that a person who has experienced success with a random event has a greater chance of further success in additional attempts.

Hyperbolic discounting

Discounting is the tendency for people to have a stronger preference for more immediate payoffs relative to later payoffs. Hyperbolic discounting leads to choices that are inconsistent over time – people make choices today that their future selves would prefer not to have made, despite using the same reasoning. Also known as current moment bias, present-bias, and related to Dynamic inconsistency.

Identifiable victim effect

The tendency to respond more strongly to a single identified person at risk than to a large group of people at risk.

IKEA effect

The tendency for people to place a disproportionately high value on objects that they partially assembled themselves, such as furniture from IKEA, regardless of the quality of the end result.

Illusion of control

The tendency to overestimate one's degree of influence over other external events.

Illusion of validity

Belief that furtherly acquired information generates additional relevant data for predictions, even when it evidently does not.

Illusory correlation

Inaccurately perceiving a relationship between two unrelated events.

Illusory truth effect

A tendency to believe that a statement is true if it is easier to process, or if it has been stated multiple times, regardless of its actual veracity. These are specific cases of truthiness.

Impact bias

The tendency to overestimate the length or the intensity of the impact of future feeling states.

Information bias

The tendency to seek information even when it cannot affect action.

Insensitivity to sample size

The tendency to under-expect variation in small samples.

Irrational escalation

The phenomenon where people justify increased investment in a decision, based on the cumulative prior investment, despite new evidence suggesting that the decision was probably wrong. Also known as the sunk cost fallacy.

Law of the instrument

An over-reliance on a familiar tool or methods, ignoring or under-valuing alternative approaches. "If all you have is a hammer, everything looks like a nail."

Less-is-better effect

The tendency to prefer a smaller set to a larger set judged separately, but not jointly.

Look-elsewhere effect

An apparently statistically significant observation may have actually arisen by chance because of the size of the parameter space to be searched.

Loss aversion

The disutility of giving up an object is greater than the utility associated with acquiring it. (see also Sunk cost effects and endowment effect).

Mere exposure effect

The tendency to express undue liking for things merely because of familiarity with them.

Money illusion

The tendency to concentrate on the nominal value (face value) of money rather than its value in terms of purchasing power.

Moral credential effect

The tendency of a track record of non-prejudice to increase subsequent prejudice.

Negativity bias or Negativity effect

Psychological phenomenon by which humans have a greater recall of unpleasant memories compared with positive memories. (see also actor-observer bias, group attribution error, positivity effect, and negativity effect).

Neglect of probability

The tendency to completely disregard probability when making a decision under uncertainty.

Normalcy bias

The refusal to plan for, or react to, a disaster which has never happened before.

Not invented here

Aversion to contact with or use of products, research, standards, or knowledge developed outside a group. Related to IKEA effect.

Observer-expectancy effect

When a researcher expects a given result and therefore unconsciously manipulates an experiment or misinterprets data in order to find it (see also subject-expectancy effect).

Omission bias

The tendency to judge harmful actions as worse, or less moral, than equally harmful omissions (inactions).

The tendency to judge a decision by its eventual outcome instead of based on the quality of the decision at the time it was made.

Overconfidence effect

Excessive confidence in one's own answers to questions. For example, for certain types of questions, answers that people rate as "% certain" turn out to be wrong % of the time.

Pareidolia

A vague and random stimulus (often an image or sound) is perceived as significant, e.g., seeing images of animals or faces in clouds, the man in the moon, and hearing non-existent hidden messages on records played in reverse.

Pessimism bias

The tendency for some people, especially those suffering from depression, to overestimate the likelihood of negative things happening to them.

Planning fallacy

The tendency to underestimate task-completion times.

Post-purchase rationalization

The tendency to persuade oneself through rational argument that a purchase was good value.

Pro-innovation bias

The tendency to have an excessive optimism towards an invention or innovation's usefulness throughout society, while often failing to identify its limitations and weaknesses.

Projection bias

The tendency to overestimate how much our future selves share one's current preferences, thoughts and values, thus leading to sub-optimal choices.

Pseudocertainty effect

The tendency to make risk-averse choices if the expected outcome is positive, but make risk-seeking choices to avoid negative outcomes.

Reactance

The urge to do the opposite of what someone wants you to do out of a need to resist a perceived attempt to constrain your freedom of choice (see also Reverse psychology).

Reactive devaluation

Devaluing proposals only because they purportedly originated with an adversary.

Recency illusion

The illusion that a word or language usage is a recent innovation when it is in fact long-established (see also frequency illusion).

Regressive bias

A certain state of mind wherein high values and high likelihoods are overestimated while low values and low likelihoods are underestimated.unreliable source?

Restraint bias

The tendency to overestimate one's ability to show restraint in the face of temptation.

Rhyme as reason effect

Rhyming statements are perceived as more truthful. A famous example being used in the O.J Simpson trial with the defense's use of the phrase "If the gloves don't fit, then you must acquit."

Risk compensation / Peltzman effect

The tendency to take greater risks when perceived safety increases.

Selective perception

The tendency for expectations to affect perception.

Semmelweis reflex

The tendency to reject new evidence that contradicts a paradigm.

Sexual overperception bias / sexual underperception bias

The tendency to over-/underestimate sexual interest of another person in oneself.

Social comparison bias

The tendency, when making hiring decisions, to favour potential candidates who don't compete with one's own particular strengths.

Social desirability bias

The tendency to over-report socially desirable characteristics or behaviours in oneself and under-report socially undesirable characteristics or behaviours.

Status quo bias

The tendency to like things to stay relatively the same (see also loss aversion, endowment effect, and system justification).

Stereotyping

Expecting a member of a group to have certain characteristics without having actual information about that individual.

Subadditivity effect

The tendency to judge probability of the whole to be less than the probabilities of the parts.

Subjective validation

Perception that something is true if a subject's belief demands it to be true. Also assigns perceived connections between coincidences.

Surrogation

Losing sight of the strategic construct that a measure is intended to represent, and subsequently acting as though the measure is the construct of interest.

Survivorship bias

Concentrating on the people or things that "survived" some process and inadvertently overlooking those that didn't because of their lack of visibility.

Time-saving bias

Underestimations of the time that could be saved (or lost) when increasing (or decreasing) from a relatively low speed and overestimations of the time that could be saved (or lost) when increasing (or decreasing) from a relatively high speed.

Third-person effect

Belief that mass communicated media messages have a greater effect on others than on themselves.

Triviality / Parkinson's Law of

The tendency to give disproportionate weight to trivial issues. Also known as bikeshedding, this bias explains why an organization may avoid specialized or complex subjects, such as the design of a nuclear reactor, and instead focus on something easy to grasp or rewarding to the average participant, such as the design of an adjacent bike shed.

Unit bias

The tendency to want to finish a given unit of a task or an item. Strong effects on the consumption of food in particular.

Weber–Fechner law

Difficulty in comparing small differences in large quantities.

Well travelled road effect

Underestimation of the duration taken to traverse oft-traveled routes and overestimation of the duration taken to traverse less familiar routes.

Zero-risk bias

Preference for reducing a small risk to zero over a greater reduction in a larger risk.

Zero-sum bias

A bias whereby a situation is incorrectly perceived to be like a zero-sum game (i.e., one person gains at the expense of another).

Social biasesedit

Most of these biases are labeled as attributional biases.

Name

Description

Actor-observer bias

The tendency for explanations of other individuals' behaviors to overemphasize the influence of their personality and underemphasize the influence of their situation (see also Fundamental attribution error), and for explanations of one's own behaviors to do the opposite (that is, to overemphasize the influence of our situation and underemphasize the influence of our own personality).

Authority bias

The tendency to attribute greater accuracy to the opinion of an authority figure (unrelated to its content) and be more influenced by that opinion.

Defensive attribution hypothesis

Attributing more blame to a harm-doer as the outcome becomes more severe or as personal or situational similarity to the victim increases.

Egocentric bias

Occurs when people claim more responsibility for themselves for the results of a joint action than an outside observer would credit them with.

Extrinsic incentives bias

An exception to the fundamental attribution error, when people view others as having (situational) extrinsic motivations and (dispositional) intrinsic motivations for oneself

False consensus effect

The tendency for people to overestimate the degree to which others agree with them.

Forer effect (aka Barnum effect)

The tendency to give high accuracy ratings to descriptions of their personality that supposedly are tailored specifically for them, but are in fact vague and general enough to apply to a wide range of people. For example, horoscopes.

Fundamental attribution error

The tendency for people to over-emphasize personality-based explanations for behaviors observed in others while under-emphasizing the role and power of situational influences on the same behavior (see also actor-observer bias, group attribution error, positivity effect, and negativity effect).

Group attribution error

The biased belief that the characteristics of an individual group member are reflective of the group as a whole or the tendency to assume that group decision outcomes reflect the preferences of group members, even when information is available that clearly suggests otherwise.

Halo effect

The tendency for a person's positive or negative traits to "spill over" from one personality area to another in others' perceptions of them (see also physical attractiveness stereotype).

Illusion of asymmetric insight

People perceive their knowledge of their peers to surpass their peers' knowledge of them.

Illusion of external agency

When people view self-generated preferences as instead being caused by insightful, effective and benevolent agents

Illusion of transparency

People overestimate others' ability to know them, and they also overestimate their ability to know others.

The tendency for people to give preferential treatment to others they perceive to be members of their own groups.

Just-world hypothesis

The tendency for people to want to believe that the world is fundamentally just, causing them to rationalize an otherwise inexplicable injustice as deserved by the victim(s).

Moral luck

The tendency for people to ascribe greater or lesser moral standing based on the outcome of an event.

Naïve cynicism

Expecting more egocentric bias in others than in oneself.

Naïve realism

The belief that we see reality as it really is – objectively and without bias; that the facts are plain for all to see; that rational people will agree with us; and that those who don't are either uninformed, lazy, irrational, or biased.

Outgroup homogeneity bias

Individuals see members of their own group as being relatively more varied than members of other groups.

Self-serving bias

The tendency to claim more responsibility for successes than failures. It may also manifest itself as a tendency for people to evaluate ambiguous information in a way beneficial to their interests (see also group-serving bias).

Shared information bias

Known as the tendency for group members to spend more time and energy discussing information that all members are already familiar with (i.e., shared information), and less time and energy discussing information that only some members are aware of (i.e., unshared information).

Sociability bias of language

The disproportionally higher representation of words related to social interactions, in comparison to words related to physical or mental aspects of behavior, in most languages. This bias attributed to nature of language as a tool facilitating human interactions. When verbal descriptors of human behavior are used as a source of information, sociability bias of such descriptors emerges in factor-analytic studies as a factor related to pro-social behavior (for example, of Extraversion factor in the Big Five personality traits

System justification

The tendency to defend and bolster the status quo. Existing social, economic, and political arrangements tend to be preferred, and alternatives disparaged, sometimes even at the expense of individual and collective self-interest. (See also status quo bias.)

Trait ascription bias

The tendency for people to view themselves as relatively variable in terms of personality, behavior, and mood while viewing others as much more predictable.

Ultimate attribution error

Similar to the fundamental attribution error, in this error a person is likely to make an internal attribution to an entire group instead of the individuals within the group.

Worse-than-average effect

A tendency to believe ourselves to be worse than others at tasks which are difficult.

CHAPTER FOUR - Inside the Exponential Organisation

Exponential Organization can be encompassed with the acronym SCALE, so too can an ExO’s internal mechanisms be expressed with the acronym IDEAS.

Interfaces

Dashboards

Experimentation

Autonomy

Social Technologies

Interfaces

Interfaces are filtering and matching processes by which ExOs bridge from SCALE externalities to internal IDEAS control frameworks.

They are algorithms and automated workflows that route the output of SCALE externalities to the right people at the right time internally.

A classic example is Google’s Ad Words, which is now a multi-billion dollar business within Google.

A key to its scalability is self-provisioning—that is, the interface for an AdWords customer has been completely automated such that there is no manual involvement.

The X Prize Foundation has created mechanisms and dedicated teams for each of its prizes.

TED has strict guidelines that help its many “franchised” TEDx events around the world deliver with consistency.

And Uber has its own ways of handling its army of drivers.

Dashboards

There has always been a tension in business created by the need to balance instrumentation and data collection versus running the company and getting things done. Collecting internal progress statistics take time, effort and expensive IT. That’s why results were usually tracked annually or, at best, quarterly.

Today’s start-ups (as well as more mature enterprises) are leveraging wireless broadband, the internet, sensors and the cloud to track this same data in real time.

Experimentation

We define Experimentation as the implementation of the Lean Start-up methodology of testing assumptions and constantly experimenting with controlled risks.

Autonomy

Valve Software, a game company, is a most unusual enterprise. It has 330 staffers but no classic management structure, reporting lines, job descriptions or regular meetings.

Instead, the company hires talented, innovative self-starters, who decide which projects they wish to join.

They are also encouraged to start new projects, so long as they fit the company’s MTP.

Autonomy is a prerequisite for permission-less innovation

Social Technologies

Social technology is finding fertile ground because the workplace has become increasingly digitised.

Social technology has 3 key objectives:

1. Reduce the distance between obtaining (and processing) information and decision making2. Migrate from having to look up information to having it flow through your perception3. Leverage community to build out ideas

From our perspective, Social Technologies are comprised of 7 key elements:

4. Beware the “Expert”

History has shown that the best inventions or solutions rarely come from experts; they almost always come from outsiders.

That is, from people who aren’t domain experts but who offer a fresh perspective.

5. Death to the Five-Year Plan

In an exponential world, the five-year plan is not only unworkable, it is seriously counterproductive, and perhaps, deadly.

The future is changing so quickly that any forward look is likely to produce false scenarios, so much so that today’s five-year plans have a high probability of offering the wrong advice.

ExOs, sees five-year plans being replaced with the following elements:

MTPs for overall guidance and emotional enrolment.

Dashboards to provide real time information on how a business is progressing.

Leveraging “Moments of Impact” for clean, productive decision-making.

One-year (at most) operating plan that is connected to the Dashboard.

6. Smaller Beats Bigger (aka Size Does Matter, Just not the Way You Think)

The answer to the question of how big an Exponential Organization can get yields yet another, more precise, question: How quickly can you convert exponential growth into the critical mass needed to become a platform?

Once that happens there is no practical limit.

7. Rent, Don’t Own

It is estimated there are now hundreds of “fablabs” operating around the world.

Soon, every town and neighbourhood will have one, meaning that any individual or small team will be able to rent equipment and be as capital-empowered as an established corporation.

Today, airlines pay for engines by the number of hours flown.

In other words, something as expensive and complex as an aircraft engine has now become a rented, pay-as-you-go asset, rather than an expensive internal business unit.

8. Trust Beats Control and Open Beats Closed

Five key precepts to Zappos that drive culture across the organization:

Vision: What you’re doing Purpose: Why you do it Business model: What will fuel you as you’re doing it Wow and uniqueness factors: What sets you apart from others Values: What matters to you

Anything predictable has been or will be automated by AI or robots, leaving the human worker to handle exceptional situations.

At Facebook, however, development teams enjoy the full trust of management.

Any team can release new code onto the live site without oversight.

As a management style, it seems counter-intuitive, but with individual reputations at stake—and no one else to catch shoddy coding—Facebook teams end up working that much harder to ensure there are no errors.

The result is that Facebook has been able to release code of unimaginable complexity faster than any other company in Silicon Valley history.

In the process, it has seriously raised the bar.

9. Everything is Measurable and anything is Knowable

We usually track our health using just three basic metrics: temperature, blood pressure and pulse rate.

Now, imagine if we could measure each one of those ten trillion cells—and not with just three metrics, but with a hundred.

We are moving toward a world in which everything will be measured and anything can be knowable, both in the world around us and within our bodies.

Only enterprises that plan for this new reality will have a chance at long-term success.

CHAPTER SIX Starting an ExO

Step 1: Select an MTP (Massive Transformative Purpose).

Begin by asking the question: What is the biggest problem I’d like to see solved?

Identify that problem space and then come up with an MTP for it.

Even as a child, Elon Musk, perhaps the world’s most celebrated entrepreneur today, had a burning desire to address energy, transportation and space travel at a global level.

His three companies (SolarCity, Tesla and SpaceX) are each addressing those spaces.

Each has a Massive Trans-formative Purpose.

It’s the burning passion to solve an obsessive, complex problem that keeps an entrepreneur pushing along the rollercoaster ride of ebullience and despair that is the story of every start-up.

Kahlil Gibran: “Work is love made visible. The goal is not to live forever; the goal is to create something that will.”

Step 2: Join or Create Relevant MTP Communities

There is a fundamental DNA path dependency here.

Are you primarily a community or are you primarily a company?

The reason you have to ask yourself this is because sooner or later the two will come in conflict. We [DIY Drones] are primarily a community.

Every day, we make decisions that disadvantage the company to bring advantage to the community.

According to Mullenweg, “Whenever this moment comes up, always bet on the community, because that’s the difference between long-term thinking and short-term thinking.”

Basically, if you get the community right, opportunities will arise. If you get community wrong, the engine of innovation dissolves and you won’t have a company anymore.

Step 3: Compose a Team

The following roles are critical if founding ExO teams are to deliver diverse backgrounds, independent thought and complementary skills:

Delivery skills: The ability to execute ideas—to analyse, plan, implement, follow through and be detail-oriented.

Step 4: Breakthrough Idea

The three key success factors for an ExO idea are:

First, a minimum 10x improvement over the status quo.

Second, leveraging information to radically cut the cost of marginal supply (i.e., the cost to expand the supply side of the business should be minimal).

Third, the idea should pass the “toothbrush test” originated by Larry Page: Does the idea solve a real customer problem or use case on a frequent basis? Is it something so useful that a user would go back to it several times a day?

Silicon Valley is littered with the carcasses of companies with great technologies searching for a problem to solve.

There is no shortage of either ideas or new technologies.

After all, everybody in a place like Silicon Valley has an idea for a new tech business.

Instead, the key to success is relentless execution, hence the need for passion and the MTP.

Entrepreneurial success rarely comes from the idea.

Instead, it comes from the founding team’s never-say-die attitude and relentless execution.

As investor Fred Wilson says, “Start-ups should be hunch-driven early on, and data-driven as they scale.”

Step 5: Build a Business Model Canvas

Business-Model-Canvas

Credit: Alexander Osterwalder.

Step 6: Find a Business Model

Eight ways to build a business model when the underlying information is free:

Immediacy: Immediacy is the reason people order in advance on Amazon or attend the theatre on opening night. Being the first to know about or experience something has intrinsic cultural, social and even commercial value. In short: time confers privilege.

Personalization: Having a product or service customised just for you not only gives added value in terms of quality of experience and ease-of-use or functionality, it also creates “stickiness,” as both parties are invested in the process.

Interpretation: Even if the product or service is free, there is still considerable added value to any service that can help shorten the learning curve to using it—or using it better. Kelly often jokes: “Software: free; the manual: $10,000.”

Authenticity: Added value comes from a guarantee that the product or service is real and safe—that it is, in Kelly’s words, “bug-free, reliable and warranted.”

Accessibility: Ownership requires management and maintenance. In an era where we own hundreds of apps on several platforms, any service that helps us organize everything and improve our ability to find what we need quickly is of particular value.Embodiment: Digital information has no “body,” no physical form, until we give it one—high definition, 3D, a movie screen, a smartphone. We willingly pay more to have free software delivered to us in the physical format we prefer.

Patronage: “It is my belief that audiences WANT to pay creators,” Kelly wrote. “Fans like to reward artists, musicians, authors and the like with tokens of their appreciation, because it allows them to connect. But they will only pay if it is very easy to do, the amount is reasonable, and they feel certain the money will directly benefit the creators.” He adds that another benefit of a simple payment process is that it capitalizes on users’ impulsiveness. Examples include iTunes songs and Spotify, as well as Netflix subscriptions. Customers choose to pay for each of these services even though the same content can be acquired through piracy.

Findability: A creative work has no value unless its potential audience can find it. Such “findability” only exists at the aggregator level, as individual creators typically get lost in the noise. Thus, attaching yourself to effective channels and digital platforms like app stores, social media sites or online marketplaces where potential users can find you has considerable value to creators (and, ultimately, to users).Step 7: Build the MVP

The MVP is a kind of applied experiment to determine the simplest product that will allow the team to go to market and see how users respond

Feedback loops can then rapidly iterate the product to optimize it and drive the feature roadmap of its development.

Step 8: Validate Marketing and Sales

Once the product is being used in its chosen market(s), a customer acquisition funnel will need to be established to help drive new visitors to the product. Its role is to qualify potential customers and convert them into users and paying customers.

Acquisition: How do users locate you? (Growth metric)

Activation: Do users have a great first experience? (Value metric)

Retention: Do users come back? (Value metric)

Revenue: How do you make money? (Value metric)

Referral: Do users tell others? (Growth metric)

Step 9: Implement SCALE and IDEAS

MTP: Formulate an MTP in a particular problem space, one that all founders feel passionate about.

Community & Crowd: Validate idea in MTP communities. Get product feedback. Find co-founders, contractors and experts. Use crowd funding and crowdsourcing to validate market demand and as a marketing technique.

Algorithms: Identify data streams that can be automated and help with product development. Implement cloud-based and open source machine and deep learning to increase insights.Leveraged Assets: Do NOT acquire assets. Use cloud computing, TechShop for product development. Use incubators like Y Combinator and Techstars for office, funding, mentoring and peer input. Starbucks as office.

Engagement: Design product with engagement in mind. Gather all user interactions. Gamify where possible. Create a digital reputational system of users and suppliers to build trust and community. Use incentive prizes to engage crowd and create buzz.

Interfaces: Design custom processes for managing SCALE; do not automate until you’re ready to scale.

Dashboards: Set up OKR and value, serendipity, and growth metrics dashboards; do not implement value metrics until product finalized (see Step 10).

Experimentation: Establish culture of experimentation and constant iteration. Be willing to fail and pivot as needed.

Autonomy: Implement lite version of Holacracy. Start with the General Company Circle as a first step; then move onto governance meetings. Implement the GitHub technical and organizational model with radical openness, transparency and permission.

Social Technologies: Implement file sharing, cloud-based document management. Collaboration and activity streams both internally and within your community. Make a plan to test and implement telepresence, virtual worlds and emotional sensing

Step 10: Establish the Culture

According to noted hotelier Chip Conley, “Culture is what happens when the boss leaves.”

Establishing a corporate culture starts with learning how to effectively track, manage and reward performance.

Step 11: Ask Key Questions Periodically

Who is your customer?

Which customer problem are you solving?

What is your solution and does it improve the status quo by at least 10x?

How will you market the product or service?

How are you selling the product or service?

How do you turn customers into advocates using viral effects and Net Promoter Scores to drive down the marginal cost of demand?

How will you scale your customer segment?

How will you drive the marginal cost of supply towards zero?

“It takes a 9x improvement to move people from incumbent products to new products from start-ups.”

Step 12: Building and Maintaining a Platform

Gather: The algorithmic process starts with harnessing data, which is gathered via sensors, people, or imported from public datasets.

Organize: The next step is to organize the data. This is known as ETL (extract, transform and load).

Apply: Once the data is accessible, algorithms such as machine or deep learning extract insights, identify trends and tune new algorithms.

Expose: The final step is exposing the data in the form of an open platform.

CHAPTER SEVEN ExOs and Mid-Market Companies

It is possible to take an established mid-market company and supercharge it to exponential growth. Examples

TED

GitHub

Coyote Logistics

Studio Roosegaarde

GoPro

CHAPTER EIGHT ExOs for Large Organizations

“Companies may promote the idea of new business creation, [but] in the end they are all in the business of reducing risk and building to scale—which is, of course, the antithesis of entrepreneurship and new ventures.”

Disruptive new ideas never map onto the traditional organization chart, and mature companies, above all else, are all about org charts.

Few companies, however, are able to transform quickly. Apple and IBM are two rare examples of large companies that have successfully undertaken an extreme transformation and executed it fairly quickly.

Four such strategies for large organizations to deploy in an accelerating business world while still keeping their core operational businesses intact:

Transform leadership.

Partner with, invest in or acquire ExOs.

Disrupt[X].

Implement ExO Lite internally.

1. Transform Leadership

Four ways to transform the leadership layers of a big company:

1. Education - Singularity University, in partnership with X Prize and Deloitte, set up a four-day workshop called the Innovation Partners Program (IPP). Every six months, eighty Fortune 500 C-Level executives receive two days of briefings on accelerating technologies, followed by two days of seminars introducing ExO-style organizational tools, including case studies, interviews and practice sessions on incentive prizes.

2. Board Management - Educate the board so that it is equipped to buy into the CEO’s plan for radical change. In addition, track your board using OKRs.

3. Implement Diversity - Sebastian Thrun, CEO of Udacity and a driving force behind the Google car, recently said, “When I’m hiring employees today, imagination is much more important than experience.” Gender: Companies with all-male boards underperformed those of mixed-gender boards by an astounding 26 percent. Recommendations: Break up bastions of old-line thinking and replace them with individuals and teams offering diversity in terms of experience and perspective. Remember that one of the most important aspects of diversity requires putting young people into positions of power and influence. In addition, include more women on your board.

4. Skills and Leadership - Recommendations: Keep diversity in mind when appointing to governance and advisory boards. Regularly take your senior leadership through a personal transformation program. Examine your own leadership skill sets. Remove anyone who puts his or her own career ahead of the success of the enterprise.2. Partner with Accelerators, Incubators and Hackerspaces

Amazon – Clearing the Rainforest of “No”:If you’re a manager at Amazon and a subordinate comes to you with a great idea, your default answer must be YES. If you want to say no, you are required to write a two-page thesis explaining why it’s a bad idea.

In other words, Amazon has increased the friction entailed in saying no, resulting in more ideas being tested (and hence implemented) throughout the company

CHAPTER TEN - The Exponential Executive

5 Likely Breakthrough Technologies:

1. Sensors and the Internet of Things - We’ll see a leap from eight billion Internet-connected devices today to fifty billion by 2020. Anything and everything will have sensors embedded, from wearables and packages to even food.

Implications: Infinite computation (as Moore’s Law continues) and infinite storage, both essentially free; the Quantified Employee; AaaS (Analytics as a Service); hardware as the new software via developments such as Arduino; new business models based on connected products.2. AI, data science and analytics - Ubiquitous usage of Machine Learning and Deep Learning algorithms to process vast caches of information.

Implications: Algorithms driving more and more business decisions; AIs replacing a large percentage of knowledge workers; AIs looking for patterns in organizational data; algorithms embedded into products.

3. Virtual/augmented reality - Avatar-quality VR available on desktop in 2-3 years. Oculus Rift, High Fidelity and Google Glass drive new applications.

Implications: The blockchain becomes a trust engine; most third-party validation functions become automated (e.g., multi-signatory contracts, voting systems, audit practices). Micro-transactions and new payment systems become ubiquitous.5. Neuro-feedback - Use of feedback loops to bring the brain to a high level of precision. Implications: Capacity to test and deploy entirely new classes of applications (e.g., focus@will); group creativity apps; flow hacking; therapeutic aids, stress reduction and sleep improvement.

These new technologies will, in turn, underpin the appearance of five likely meta-trends:

5 Likely Meta-Trends:

1. Perfect knowledge:

Implications: With the Internet of (Every)thing, sensors, low Earth orbit (LEO) satellite systems and unlimited sensors, users will be able to know anything they want, anywhere and at any time.

2. Virtual worlds

Implications: Philip Rosedale notes that Hollywood special effects migrate to the desktop after five years.

Avatar is now three years old and will soon be available on the Oculus Rift.

Almost perfect VR is around the corner, and will deliver experiential reality and transform retail, travel, and living and working environments.3. 3D printing

Implications: 3D printing (and soon 4D) will not radically change big manufacturing, but it will enable an entirely new class of products that will displace traditional manufacturing. A Kinko’s model of local 3D printing of virtually anything will appear shortly and the technology will have a major impact on warehousing and transportation. U.S. manufacturing will be revitalized as recent offshoring trends reverse.

4. Disruption of payment systems

Implications: In 2012, Visa and MasterCard credit card purchases totalled more than $1.5 trillion in the U.S. alone.

Payment systems and money transfer mechanisms haven’t changed for decades, but with Square, PayPal and now Clinkle and Bitcoin, this domain is ready for a major transformation.

One form will come via mobile/social wallets and seamless transactions.

A second will come via micropayments (probably via the block chain).

The ability to move infinitesimal transaction amounts will underpin entirely new business models.5. Autonomous vehicles

Implications: In September 2014, California will issue the first license plates for driverless cars. Starting with delivery vehicles and then taxis, predictions call for existing road capacity to increase 8-10 times once a critical mass of AVs is reached.

Ridesharing is an intermediate step toward fully automated transportation, which may have a bigger visible impact on society than anything else, including sustainability, urban planning (almost no parking lots) and fewer traffic fatalities.